AI Predicts Autism From Infant Brain Scans

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    Profile photo of Anna Clark
    Anna Clark

    IEEE Spectrum, 2/15/2017

    Researchers at the University of North Carolina, Chapel Hill have applied deep-learning algorithms to brain scans of children with a high risk of autism. Algorithms used three indicators, brain surface area, volume, and the gender of the child, to determine if 6- to 12-month-old infants were likely to develop autism. The results were 81% accurate at predicting later diagnosis. This improves over a 50% prediction rate from behavioral questionnaires.

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